May 02, 2016
This blog post is a work in progress and will detail the process that I took to create the Visaurant project.
Visaurant (as you can see in the video below) is a reimagination of the way users search through images that they are interested in. One prime use case for Visaurant is in sorting and filtering through food images (hence VIS -ual rest- AURANT).
So why do we want a visual search application?
Images represent a wealth of information. As cliche as it sounds, 'a picture is worth a thousand words' especially when it comes to looking for food items that seem appetizing. Speaking from personal experience, I often use apps like Yelp by:
- Going to the images of a particular restaurant
- Looking for the pictures that look good
- Reading the caption
- Going back to the reviews to find the reviews regarding the item that I saw
While this process works, it is by no means streamlined. Having to go back and forth between the images, captions, and reviews is a hassle and quite often overwhelming because there are so many images to sift through. So although images are powerful and contain a lot of information, if the images are not ordered or organized then it becomes difficult to find what I care about (like the example below...).
Visaurant aims to change that by:
- Clustering visually similar images to allow users to quickly narrow down to images of interest
- Parsing through captions to extract reviews that are relevant to the image that was selected
What is happening in the video?
- User gets to select a group of images from a restaurant that looks interesting (4 selections)
- Recommendations will be made based on the user's selections
- User can once again select the restaurant that looks most appealing
- Restaurant specific page will show up allowing the user to hover over images that look interesting and images within the same visual cluster will be highlighted
- User can select an image and all images will be filtered for images in the same cluster
- After filtering down to a single cluster, user can select a specific image to bring up reviews that have matching words with the image's caption